A global data and secure data environment framework supporting healthcare decision-making

Executive summary

Presented at ISPOR Europe 2024, and authored by Khedidja Hedna, Pascal Sempe, Louise Murphy, and Alexander Ide, this poster outlines our global Secure Data Environment (SDE) framework, designed to power Real-World Evidence (RWE) generation across hospitals, biobanks, and research centers. With over 90 data partners spanning six continents and 80 million patient records, the platform enables secure, compliant, and scalable access to Real-World Data (RWD) for healthcare decision-making, drug development, and precision medicine research.

Objectives

The growing demand for robust RWE in healthcare decision-making, has prompted the development of SDE. The SDE developed by BC Platforms hosts deidentified RWD from hospitals, biobanks, and research centers, and aims to facilitate health technology assessments and post-launch evidence generation. This work elucidates the functionalities of the SDE and how it fosters the generation of RWE pertaining to standard of care and patients’ outcomes. 

Methods

The SDE provides remote, web-access to data adhering to the Five Safes model for privacy (Safe People, Projects, Settings, Data, and Outputs). It offers multiple deployment options: on-premises setups at hospital/biobank sites, utilization of national high-performance computer clusters, and integration with major cloud providers. The deployment options are designed to comply with local, regional, and national data governance regulations such as GDPR, HIPAA and EHDS. Structured RWD encompasses demographics, healthcare encounters, prescribed medications, hospital admissions, International Classification of Diseases diagnoses, genomics, proteomics, diagnostic methods, and imaging data. 

Results

At the time of presentation in May 2024, BC Platforms encompassed a network of over 90 data partners across six continents. The Data Network covers a catchment of 80 million subjects with clinical data and 500,000 subjects with linked clinical-genomic data. The covered therapeutic areas include oncology, haematology, neurology, metabolic disorders, cardiovascular diseases, autoimmune conditions, and rare diseases. 

Note: These figures have since evolved as BC Platforms’ global data network continues to expand.

Conclusion

This expansive Data and SDE technology framework enable the creation of representative cohorts for drug development and is currently tested for applying machine learning models to explore drug repurposing opportunities. It allows to aggregate multimodal RWD, gathered during patient care with the potential to uncover biological signals, and to assess test pathways that reflect standard of care. This structure is instrumental in developing comparator groups for clinical utility and cost consequence analyses, particularly relevant for precision medicine and rare diseases.